A Stem-Cell Based Bioassay to Critically Assess the Pathology of Dysfunctional Neuromuscular Junctions
Bibliographic record
Abstract
Pluripotent stem cells can be directed to differentiate into motor neurons and assessed for functionality in vitro. An emerging application of this technique is to model genetically inherited diseases in differentiated motor neurons and to screen for new therapeutic targets. The neuromuscular junction (NMJ) is essential to the functionality of motor neurons and its dysfunction is a primary hallmark of motor neuron disease. However, mature NMJs that possess the functional and morphological characteristics of those formed in vivo have so far not been obtained in vitro. Here we describe the generation and analysis of mature NMJs formed between embryonic stem cell-derived motor neurons (ESCMNs) and primary myotubes. We compared the formation and maturation of NMJs generated by wild-type (NCAM+/+) ESCMNs to those generated by neural cell adhesion molecule null (NCAM-/-) ESCMNs in order to definitively test the sensitivity of this assay to identify synaptic pathology. We find that co-cultures using NCAM-/- ESCMNs replicate key in vivo NCAM-/- phenotypes and reveal that NCAM influences neuromuscular synaptogenesis by controlling the mode of synaptic vesicle endocytosis. Further, we could improve synapse formation and function in NCAM-/- co-cultures by chronic treatment with nifedipine, which blocks an immature synaptic vesicle recycling pathway. Together, our results demonstrate that this ESCMN/myofiber co-culture system is a highly sensitive bioassay for examining molecules postulated to regulate synaptic function and for screening therapeutics that will improve the function of compromised NMJs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".